import tensorflow as tf
import numpy as np

# creatge data
x_data = np.random.rand(100).astype(np.float32)
# y = 0.1x +0.3
y_data = x_data * 0.1 + 0.3

# create tensorflow structure start

Weights = tf.Variable(tf.random_uniform([1], -1.0, 1.0))
biases = tf.Variable(tf.zeros([1]))

y = Weights * x_data + biases

loss = tf.reduce_mean(tf.square(y - y_data))
optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(loss)

# init = tf.initialize_all_varialbes()
init = tf.global_variables_initializer()  # 替换成这样就好
#  create tensorflow structure end


sess = tf.Session()
sess.run(init)

print(sess.run(Weights))

for step in range(201):
    sess.run(train)
    if step % 20 == 0:
        print (step,sess.run(Weights),sess.run(biases))
